As a Staff Data Scientist focused on Ad Measurement Products, you will lead the design and validation of sophisticated methods to measure advertising impact through causal inference, incrementality, and machine learning. Your work will directly shape how advertisers assess the value of their campaigns, ensuring accuracy, scalability, and scientific integrity across first- and third-party measurement solutions.
Key Responsibilities
- Develop and refine models for conversion lift, brand lift, matched-market testing, and other incrementality frameworks.
- Integrate AI and machine learning into measurement workflows to enhance speed, insight generation, and decision support for advertisers.
- Identify and mitigate risks such as data bias, imbalance, and under-powered studies, particularly in AI-driven systems.
- Collaborate with Product and Engineering teams to embed scientific insights into product roadmaps, including anomaly detection, model diagnostics, and automated reporting.
- Partner with external vendors and platforms—including clean rooms, conversion APIs, MMM, and MTA providers—to evaluate and co-develop measurement solutions.
- Define success metrics for measurement products and build frameworks that empower teams and clients to make data-driven decisions.
- Mentor data scientists and analysts, promoting best practices in statistical rigor and experimental design.
- Communicate technical tradeoffs and limitations of AI-based approaches clearly to executives, stakeholders, and external partners.
Qualifications
- 8+ years of experience applying scientific methods to large-scale data problems, with at least 5 years focused on ad measurement and incrementality.
- Proven expertise in SQL and a scripting language such as Python or R.
- Track record of translating ambiguous business questions into structured analyses that balance scientific precision with practical impact.
- Hands-on experience with AI/ML applications in measurement, experimentation, or analytics.
- Strong judgment in assessing AI-generated outputs for reliability, explainability, and scientific validity.
- Leadership in technical projects and influence across data science teams, including mentoring peers.
- Excellent communication skills with experience engaging cross-functional teams and leadership.
Work Environment
This role operates in a hybrid model, requiring weekly in-person collaboration at one of the designated offices in San Francisco, Palo Alto, or Seattle. Remote work is supported for candidates within commuting distance. The organization supports a flexible, inclusive culture that values innovation, diverse perspectives, and AI-augmented problem solving. Compensation includes a base salary range of $164,695–$339,078 USD and equity eligibility. All qualified applicants are considered without regard to race, gender, disability, or other protected characteristics.
